• Performing original quantitative research on large, complex data sets, including acquisition of domain knowledge, determination of important research questions, data collection and manipulation, statistical analysis, validation and visualization of data, and presentation of findings
• Applying machine learning techniques, in core subject including: money laundering and terrorism financing
• Selecting features, building and optimizing classifiers using machine learning techniques
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Working cross-functionally with business managers/product managers/engineers and designers
• Conducting data analysis and moderately complex designs algorithm.
• Developing predictive models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions.
• Creating models by applying robust predictive/prescriptive modeling methodologies.
• 2 to 8 years of relevant experience.
• Work experience in related field (AI, Math, Engineering or CompSci)
• Practical knowledge of Python and text/data processing packages, e.g. pandas, numpy, scikit-learn, nltk
• Experience with machine learning applications and algorithms, e.g. Linear/Logistic Regression, Neural Nets, Deep Learning, Hidden Markov Models, Naive Bayes, Game Theory.
What will gain extra points
• Knowledge of Spark ML/MLLib
• Practical skills in Natural Language Processing
• Knowledge of graph databases such as Neo4J
• Good knowledge of Java
• The opportunity for professional development and advancement.
• Work with the latest technologies
• The opportunity to work on projects with multinational banks and government agencies within APAC, Europe and USA.
• Working with a passionate, international team of enthusiasts from Europe and US.
• A huge learning opportunity - from large system integrations to AI